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In computer science, garbage in, garbage out (GIGO) is the concept that flawed, biased or poor quality ("garbage") information or input produces a result or output of similar ("garbage") quality. The adage points to the need to improve data quality in, for example, programming.
Garbage in, garbage out, or GIGO, refers to the idea that in any system, the quality of output is determined by the quality of the input. For example, if a mathematical equation is improperly stated, the answer is unlikely to be correct.
Aug 18, 2023 · “Garbage In, Garbage Out” (GIGO) is a concept in information technology and computer science that emphasizes the importance of input quality. It implies that if the data input into a system is flawed or inaccurate, the resulting output will also be flawed or inaccurate.
Feb 5, 2024 · The principle “Garbage In, Garbage Out” (GIGO) asserts the essential link between input data quality and output reliability, emphasizing the need for careful data validation. Rooted in computing history, its relevance spans across fields, advocating for meticulous data handling to ensure accurate outcomes. Origin and Etymology.
What does the saying 'Garbage in, garbage out' mean? Idiom: Garbage in, garbage out. Meaning: If a computer system or database is built badly, then the results will be bad. Country: International English | Subject Area: Technology & science | Usage Type: Both or All Words Used. Contributor: Emily.
Jan 4, 2017 · Garbage in, garbage out (GIGO), in the context of information technology, is a slang expression that means regardless of how accurate a program’s logic is, the results will be incorrect if the input is invalid.
Dec 5, 2022 · Used of computer data, the phrase garbage in, garbage out, and its abbreviation GIGO, mean: incorrect or poor-quality input will produce faulty output. This phrase and its abbreviation have come to be also applied to processes likened to computerised data processing.
Oct 27, 2023 · The concept of “garbage in, garbage out” (GIGO) is what it sounds like: If you feed your model garbage, you will get garbage. Put another way, in data and analytics and in life, “you are what you eat.”
Nov 5, 2021 · “Garbage in, garbage out” is a classic saying in computing about how problematic input data or instructions will produce problematic outputs (Babbage, 1864; Mellin, 1957), which is especially relevant in ML.
Collect the garbage from your house before it is thrown into the dustbin. Separate it into two groups, so that they have: Group 1: Garbage from the kitchen — like fruit and vegetable peels, egg shells, waste food, tea leaves. Include newspapers, dry leaves and paper bags in this group.
